Comprehension of Ads-supported and Paid Android Applications: Are They Different?

The Android market is a place where developers offer paid and-or free apps to users. Free apps are interesting to users because they can try them immediately without incurring a monetary cost. However, free apps often have limited features and-or contain ads when compared to their paid counterparts. Thus, users may eventually need to pay to get additional features and-or remove ads. While paid apps have clear market values, their ads-supported versions are not entirely free because ads have an impact on performance. In this paper, first, we perform an exploratory study about ads-supported and paid apps to understand their differences in terms of implementation and development process. We analyze 40 Android apps and we observe that (i) ads-supported apps are preferred by users although paid apps have a better rating, (ii) developers do not usually offer a paid app without a corresponding free version, (iii) ads-supported apps usually have more releases and are released more often than their corresponding paid versions, (iv) there is no a clear strategy about the way developers set prices of paid apps, (v) paid apps do not usually include more functionalities than their corresponding ads-supported versions, (vi) developers do not always remove ad networks in paid versions of their ads-supported apps, and (vii) paid apps require less permissions than ads-supported apps. Second, we carry out an experimental study to compare the performance of ads-supported and paid apps and we propose four equations to estimate the cost of ads-supported apps. We obtain that (i) ads-supported apps use more resources than their corresponding paid versions with statistically significant differences and (ii) paid apps could be considered a most cost-effective choice for users because their cost can be amortized in a short period of time, depending on their usage.Comment: Accepted for publication in the proceedings of the IEEE International Conference on Program Comprehension 201

Reputation aware obfuscation for mobile opportunistic networks

© 2013 IEEE. Current anonymity techniques for mobile opportunistic networks typically use obfuscation algorithms to hide node's identity behind other nodes. These algorithms are not well suited to sparse and disconnection prone networks with large number of malicious nodes and new opportunistic, adaptive. So, new, opportunistic, adaptive fully localized mechanisms are needed for improving user anonymity. This paper proposes reputation aware localized adaptive obfuscation for mobile opportunistic networks that comprises of two complementary techniques: opportunistic collaborative testing of nodes' obfuscation behaviour (OCOT) and multidimensional adaptive anonymisation (AA). OCOT-AA is driven by both explicit and implicit reputation building, complex graph connectivity analytics and obfuscation history analyses. We show that OCOT-AA is very efficient in terms of achieving high levels of node identity obfuscation and managing low delays for answering queries between sources and destinations while enabling fast detection and avoidance of malicious nodes typically within the fraction of time within the experiment duration. We perform extensive experiments to compare OCOT-AA with several other competitive and benchmark protocols and show that it outperforms them across a range of metrics over a one month real-life GPS trace. To demonstrate our proposal more clearly, we propose new metrics that include best effort biggest length and diversity of the obfuscation paths, the actual percentage of truly anonymised sources' IDs at the destinations and communication quality of service between source and destination

CAMEO: A Middleware for Mobile Advertisement Delivery

National Research Foundation (NRF) Singapor

Design and Analysis of an Efficient Friend-to-Friend Content Dissemination System

International audienceOpportunistic communication, off-loading and decentrlaized distribution have been proposed as a means of cost efficient disseminating content when users are geographically clustered into communities. Despite its promise, none of the proposed systems have not been widely adopted due to unbounded high content delivery latency, security and privacy concerns. This paper, presents a novel hybrid content storage and distribution system addressing the trust and privacy concerns of users, lowering the cost of content distribution and storage, and shows how they can be combined uniquely to develop mobile social networking services. The system exploit the fact that users will trust their friends, and by replicating content on friends’ devices who are likely to consume that content it will be possible to disseminate it to other friends when connected to low cost networks. The paper provides a formal definition of this content replication problem, and show that it is NP hard. Then, it presents a community based greedy heuristic algorithm with novel dynamic centrality metrics that replicates the content on a minimum number of friends’ devices, to maximize availability. Then using both real world and synthetic datasets, the effectiveness of the proposed scheme is demonstrated. The practicality of the proposed system, is demonstrated through an implementation on Android smartphones

An Evaluation of Smartphone Resources Used by Web Advertisements

With the rapid advancement of mobile devices, people have become more attached to them than ever. This rapid growth combined with millions of applications (apps) make smartphones a favourite means of communication among users. In general, the available contents on smartphones, apps and the web, come into two versions: (i) free contents that are monetized via advertisements (ads), and (ii) paid ones that are monetized by user subscription fees. However, the resources (energy, bandwidth, processing power) on-board are limited, and the existence of ads in either websites or free apps can adversely impact these resources. These issues brought the need for good understanding of the mobile advertising eco-system and how such limited resources can be efficiently used. This thesis focuses on mobile web browsing. Surfing web-pages on smatphones is one of the most commonly used task among smartphone users. However, web-page complexity is increasing, especially when designed for desktop computers. On one hand, the existence of ads in web-pages is essential for publishers' monetization strategy. On the other hand, their existence in webpages leads to even higher complexity of the webpages. This complexity in the smartphone environment, where the battery and bandwidth resources are limited, is reflected in longer loading time, more energy consumed, and more bytes transferred. With this view, quantifying the energy consumption due to web ads in smartphones is essential for publishers to optimize their webpages, and for system designers to develop an energy-aware applications (browsers) and protocols. Apart from their energy impact, ads consume network bandwidth as well. Therefore, quantifying the bandwidth consumption due to downloading web ads is crucial to creating more energy and bandwidth aware applications. This thesis first classifies web content into: (i) core information, and (ii) forced ``unwanted" information, namely ads. Then, describes an approach that enables the separation of web content in a number of a websites. Having done so, the energy cost due to downloading, rendering, and displaying web ads over Wi-Fi and 3G networks is evaluated. That is, how much energy web ads contribute to the total consumed energy when a user accesses the web. Furthermore, the bandwidth consumed by web ads in a number of well-known websites is also evaluated. Motivated by our findings about ads' impact on the energy and bandwidth, the thesis proposes and implements a novel web-browsing technique that adapts the webpages delivered to smartphones, based on a smartphone's current battery level and the network type. Webpages are adapted by controlling the amount of ads to be displayed. Validation tests confirm that the system, in some cases, can extend smartphone battery life by up to ~ 30\% and save wireless bandwidth up to ~ 44\%

Mitigating the True Cost of Advertisement- Supported “Free ” Mobile Applications

The dominant, “ad-supported free application ” model for consumeroriented mobile computing is seemingly imperiled by the growing global adoption of metered data pricing plans by mobile operators. In this paper, we explore the opportunities for addressing this emerging conflict by enabling more intelligent ad delivery to such mobile devices. One especially promising path is leveraging the increasing availability of heterogeneous wireless access technologies (e.g., WiFi, femtocells) that offer less restrictive and more energy-efficient transport substrates for such data traffic. To understand the possibilities that exist, we first profile the advertisement traffic characteristics for some of the most popular advertisement-supported consumer applications, and then analyze the key features of mobile advertisement delivery. We then outline the principles of CAMEO, a middleware that uses predictive profiling of a user’s {device, network and usage} context to anticipate the advertisements that need to be served, and then modulates their delivery mechanism to enable effective mobile advertising, but at considerably lower costs

Assisting Developers and Users in Developing and Choosing Efficient Mobile Device Apps

Les applications pour appareils mobiles jouent, de nos jours, un rôle important dans nos vies. Même si la consommation énergétique affecte la durée de vie de la batterie des appareils mobiles et limite l’utilisation des appareils, nous les utilisons presque partout, tout le temps et pour presque tout. Avec la croissance exponentielle du marché des applications pour appareils mobiles, les développeurs ont été témoins d’un changement radical dans le paysage du développement du logiciel. Les applications mobiles présentent de nouveaux défis dans la conception et l’implantation logicielle dus aux contraintes des ressources internes (tel que la batterie, le CPU et la mémoire) et externes (l’utilisation de donnés). Donc, les exigences traditionnelles non-fonctionnelles, tels que la fonctionnalité et la maintenabilité, ont été éclipsées par la performance. Les chercheurs étudient activement le rôle des pratiques de codage sur la consommation énergétique. Cependant, le CPU, la mémoire et les utilisations du réseau sont aussi des mesures importantes pour la performance. Même si le matériel informatique des appareils mobiles s’est beaucoup amélioré dans les dernières années, des nouveaux utilisateurs arrivent, possèdant des appareils bas de gamme avec accès limité aux données. Les développeurs doivent donc gérer les ressources attentivement car les nouveaux marchés possèdent une part importante des nouveaux utilisateurs qui se connectent en ligne pour la première fois. La performance des applications pour les appareils mobiles est donc un sujet très important. Des études récentes suggèrent que les ingénieurs logiciels peuvent aider à réduire la consommation énergétique en tenant compte des impacts de leurs décisions de conception et d’implantation sur l’énergie. Mais les décisions des développeurs ont un impact aussi sur le CPU, la mémoire et l’usage du réseau. Les développeurs doivent aussi prendre en considération la performance au moment d’évoluer le design de l’application des appareils mobiles. Le problème est que les développeurs n’ont pas de soutien pour comprendre l’impact de leurs décisions sur la performance de leurs apps. Ce problème est aussi vrai pour les utilisateurs d’appareils mobiles qui installent des apps en ignorant s’il existe des alternatives plus efficaces. Dans cette dissertation, nous aidons les développeurs et les utilisateurs à connaitre d’avantage l’impact de leurs décisions sur la performance des applications qu’ils développent et qu’ils consomment. Nous voulons aider les développeurs et les utilisateurs à développer et choisir des applications performantes. Nous fournissons des observations, des techniques et des lignes directrices qui aiderons les développeurs à prendre des décisions informées pour améliorer la performance de leurs applications. Nous proposons aussi une approche qui peut servir de complément aux marchés des applications pour appareils mobiles pour qu’ils puissent aider les développeurs et les utilisateurs à chercher des applications efficientes. Notre contribution est un pas précieux vers l’ingénierie de logiciels performants pour les applications des appareils mobiles et un avantage pour les utilisateurs d’appareils mobiles qui veulent utiliser des applications performantes.----------ABSTRACT: Mobile device applications (apps) play nowadays a central role in our life. Although energy consumption affects battery life of mobile devices and limits device use, we use them almost anywhere, all the time, and for almost everything. With the exponential growth of the market of mobile device apps in recent years, developers have witnessed a radical change in the landscape of software development. Mobile apps introduce new challenges in software design and implementation due to the constraints of internal resources (such as battery, CPU, and memory), as well as external resources (as data usage). Thus, traditional non-functional requirements, such as functionality and maintainability, have been overshadowed by performance. Researchers are actively investigating the role of coding practices on energy consumption. However, CPU, memory, and network usages are also important performance metrics. Although the hardware of mobile devices has considerably improved in recent years, emerging market users own low-devices and have limited access to data connection. Therefore, developers should manage resources mindfully because emerging markets own a significant share of the new users coming on-line for the first time. Thus, the performance of mobile device apps is a very important topic. Recent studies suggest that software engineers can help reduce energy consumption by considering the energy impacts of their design and implementation decisions. But developers’decisions also have an impact on CPU, memory, and network usages. So that, developers must take into account performance when evolving the design of mobile device apps. The problem is that mobile device app developers have no support to understand the impact of their decisions on their apps performance. This problem is also true for mobile device users who install apps ignoring if there exist more efficient alternatives. In this dissertation we help developers and users to know more about the impact of their decisions on the performance of apps they develop and consume, respectively. Thus, we want to assist developers and users in developing and choosing, respectively, efficient mobile device apps. We provide observations, techniques, and guidelines to help developers make informed decisions to improve the performance of their apps. We also propose an approach to complement mobile device app marketplaces to assist developers and users to search for efficient apps. Our contribution is a valuable step towards efficient software engineering for mobile device apps and a benefit for mobile device users who want to use efficient apps

Resource-Efficient Wireless Systems for Emerging Wireless Networks

As the wireless medium has become the primary source of communication and Internet connectivity, and as devices and wireless technologies become more sophisticated and capable, there has been a surge in the capacity demands and complexity of applications that run over these wireless devices. To sustain the volume and QoE guarantees of the data generated, the opportunity and need to rethink wireless network design across all the layers of the protocol stack has firmly emerged as a solution to enable the timely and reliable delivery of data, while handling the inherent challenges of a crowded wireless medium, such as congestion, interference, and hidden terminals. The research work presented in this dissertation builds efficient solutions and protocols with a theoretical foundation to address the challenges that arise in rethinking wireless network design. Example challenges include managing the overhead associated with complex systems. My work particularly focuses on the opportunities and challenges of sophisticated technology and systems in emerging wireless networks. I target the main thrusts in the evolution of wireless networks that create significant opportunity to achieve higher theoretical capacity, and have direct implications on our day-to-day wireless interactions: from enabling multifold increase in capacity in wireless physical links, to developing medium access techniques to exploit the high speed links, and making the applications more bandwidth efficient. I build deployable, and resource-aware wireless systems that exploit higher bandwidths by leveraging and advancing diverse research areas such as theory, analysis, protocol design, and wireless networking. Specifically, I identify the erroneous assumptions and fundamental limitations of existing solutions in capturing the true and complex interactions between wireless devices and protocols. I use these insights to guide practical and efficient protocol design, followed by thorough analysis and evaluation in testbed implementations via prototypes and measurements. I show that my proposed solutions achieve significant performance gains, at minimum cost to overhead